286 citations · 384 across the 34 of their papers we have counts for
10 papers · 1 filter
Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Bag-Level Classifier is a Good Instance-Level Teacher
Hongyi Wang, Luyang Luo, Fang Wang +5
Multiple Instance Learning (MIL) has demonstrated promise in Whole Slide Image (WSI) classification. However, a major challenge persists due to the high computational cost associat…
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor Segmentation
Jiaxin Zhuang, Luyang Luo, Zhixuan Chen +1
Deep-learning (DL) based methods are playing an important role in the task of abdominal organs and tumors segmentation in CT scans. However, the large requirements of annotated dat…
Deep Omni-supervised Learning for Rib Fracture Detection from Chest Radiology Images
Zhizhong Chai, Luyang Luo, Huangjing Lin +2
Deep learning (DL)-based rib fracture detection has shown promise of playing an important role in preventing mortality and improving patient outcome. Normally, developing DL-based…
Advancing Volumetric Medical Image Segmentation via Global-Local Masked Autoencoder
Jia-Xin Zhuang, Luyang Luo, Hao Chen
Masked autoencoder (MAE) is a promising self-supervised pre-training technique that can improve the representation learning of a neural network without human intervention. However,…
Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images
Yanwen Li, Luyang Luo, Huangjing Lin +2
Convolutional Neural Networks (CNNs) have shown remarkable progress in medical image segmentation. However, lesion segmentation remains a challenge to state-of-the-art CNN-based al…
Scale Federated Learning for Label Set Mismatch in Medical Image Classification
Zhipeng Deng, Luyang Luo, Hao Chen
Federated learning (FL) has been introduced to the healthcare domain as a decentralized learning paradigm that allows multiple parties to train a model collaboratively without priv…